From the course: CompTIA SecAI+ (CY0-001) Cert Prep
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Model access controls
From the course: CompTIA SecAI+ (CY0-001) Cert Prep
Model access controls
Controlling model access is one of the most fundamental steps in protecting an AI system. It determines who can use the model, what they can do with it, and how they connect to it. Without strong access controls, even the most secure model architecture can be compromised through unauthorized use, misuse, or outright theft. The first line of defense is authentication. Every user or system that interacts with an AI model should have valid credentials before any request is processed. For internal systems, this often means integrating with existing identity management solutions like single sign-on or active directory. For external access, organizations can issue unique API keys to each client and reject any request that lacks a valid key. These approaches ensure that only verified users can reach the model and that actions can be traced back to responsible parties. Role-based access control, also known as RBAC, or attribute-based access control, or ABAC, add an important layer of security…
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Contents
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The AI lifecycle1m 39s
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Business alignment in the AI lifecycle1m 43s
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Data collection2m 20s
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Data preparation3m 15s
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Model development and selection2m 13s
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Model evaluation and validation2m 29s
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Model deployment and integration3m 25s
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Monitoring and maintenance3m 19s
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Manipulating application integrations4m 8s
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AI supply chain attacks2m 4s
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Insecure plug-in design2m 9s
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Insecure output handling1m 23s
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Output integrity attacks2m 8s
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Model denial of service1m 31s
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Excessive agency1m 33s
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Overreliance1m 34s
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AI hallucinations1m 4s
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Monitoring prompts and responses2m 51s
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Log monitoring4m 30s
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Rate and cost monitoring5m 1s
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Auditing for AI hallucinations3m 33s
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Auditing for accuracy3m 29s
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Auditing for bias and fairness4m 35s
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Auditing access and security compliance3m 48s
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Responsible AI5m 29s
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AI risks2m 23s
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Introduction of bias2m 37s
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Accidental data leakage2m 53s
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Reputational loss2m 11s
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Accuracy and performance of the model2m 22s
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Intellectual property risks3m 31s
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Autonomous systems2m 27s
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Shadow IT and shadow AI1m 48s
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Awareness training2m 21s
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